Function load_coco_fvq_weights

src/models/vevo2/components.cpp:717–750

    return weights;
}

std::shared_ptr<const Vevo2CocoTokenizerWeights> load_coco_tokenizer_weights(
    const Vevo2CocoTokenizerConfig & config,
    const char * name,
    ggml_backend_t backend,
    engine::core::BackendType backend_type,
    size_t weight_context_bytes,
    engine::assets::TensorStorageType matmul_storage_type,
    engine::assets::TensorStorageType conv_storage_type,
    const engine::assets::TensorSource & source) {
    if (config.coco_type != "style" && config.coco_type != "content_style") {
        throw std::runtime_error("Vevo2 Coco tokenizer weights require style or content_style config");
    }
    auto weights = std::make_shared<Vevo2CocoTokenizerWeights>();
    weights->store = std::make_shared<engine::core::BackendWeightStore>(
        backend,
        backend_type,
        std::string("vevo2.") + name + ".weights",
        weight_context_bytes);
    if (config.coco_type == "content_style") {
        weights->whisper_input = engine::modules::binding::linear_from_source(
            *weights->store,
            source,
            "whisper_input_layer",
            matmul_storage_type,
            config.hidden_size,
            config.whisper_dim,
            true);
    }
    weights->chromagram_input = engine::modules::binding::linear_from_source(
        *weights->store,
        source,
        "chromagram_input_layer",
        matmul_storage_type,
        config.hidden_size,
        config.chromagram_dim,
        true);